АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ
Business process modeling is an important part of organizational management since it enables companies to obtain insights into their operational workflows and find opportunities for development. However, evaluating and quantifying the similarity of multiple business process models can be difficult b...
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| Format: | Article |
| Language: | English |
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National Technical University Kharkiv Polytechnic Institute
2023-07-01
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| Series: | Вісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології |
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| Online Access: | http://samit.khpi.edu.ua/article/view/284718 |
| _version_ | 1797779201193934848 |
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| author | Kopp Andrii Dmytro Orlovskyi |
| author_facet | Kopp Andrii Dmytro Orlovskyi |
| author_sort | Kopp Andrii |
| collection | DOAJ |
| description | Business process modeling is an important part of organizational management since it enables companies to obtain insights into their operational workflows and find opportunities for development. However, evaluating and quantifying the similarity of multiple business process models can be difficult because these models frequently differ greatly in terms of structure and nomenclature. This study offers an approach that uses natural language processing techniques to evaluate the similarity of business process models in order to address this issue. The algorithm uses the activity labels given in the business process models as input to produce textual descriptions of the associated business processes. The algorithm includes various preprocessing stages to guarantee that the textual descriptions are correct and consistent. First, single words are retrieved and transformed to lower case from the resulting textual descriptions. After that, all non-alphabetic and stop words are removed from the retrieved words. The remaining words are then stemmed, which includes reducing them to their base form. The algorithm evaluates the similarity of distinct business process models using similarity measures, including Jaccard, Sorensen – Dice, overlap, and simple matching coefficients, after the textual descriptions have been prepared and preprocessed. These metrics provide a more detailed understanding of the similarities and differences across various business process models, which can then be used to influence decision-making and business process improvement initiatives. The software implementation of the proposed algorithm demonstrates its usage for similarity measurement in a database of business process models. Experiments show that the developed algorithm is 31% faster than a search based on the SQL LIKE clause and allows finding 18% more similar models in the business process model database. |
| first_indexed | 2024-03-12T23:28:14Z |
| format | Article |
| id | doaj.art-8b3cd2ad1def4c5f8cafa6605a9a4094 |
| institution | Directory Open Access Journal |
| issn | 2079-0023 2410-2857 |
| language | English |
| last_indexed | 2024-03-12T23:28:14Z |
| publishDate | 2023-07-01 |
| publisher | National Technical University Kharkiv Polytechnic Institute |
| record_format | Article |
| series | Вісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології |
| spelling | doaj.art-8b3cd2ad1def4c5f8cafa6605a9a40942023-07-15T15:41:38ZengNational Technical University Kharkiv Polytechnic InstituteВісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології2079-00232410-28572023-07-011 (9)545910.20998/2079-0023.2023.01.08322942АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВKopp Andrii0https://orcid.org/0000-0002-3189-5623Dmytro Orlovskyi1https://orcid.org/0000-0002-8261-2988National Technical University "Kharkiv Polytechnic Institute"National Technical University "Kharkiv Polytechnic Institute"Business process modeling is an important part of organizational management since it enables companies to obtain insights into their operational workflows and find opportunities for development. However, evaluating and quantifying the similarity of multiple business process models can be difficult because these models frequently differ greatly in terms of structure and nomenclature. This study offers an approach that uses natural language processing techniques to evaluate the similarity of business process models in order to address this issue. The algorithm uses the activity labels given in the business process models as input to produce textual descriptions of the associated business processes. The algorithm includes various preprocessing stages to guarantee that the textual descriptions are correct and consistent. First, single words are retrieved and transformed to lower case from the resulting textual descriptions. After that, all non-alphabetic and stop words are removed from the retrieved words. The remaining words are then stemmed, which includes reducing them to their base form. The algorithm evaluates the similarity of distinct business process models using similarity measures, including Jaccard, Sorensen – Dice, overlap, and simple matching coefficients, after the textual descriptions have been prepared and preprocessed. These metrics provide a more detailed understanding of the similarities and differences across various business process models, which can then be used to influence decision-making and business process improvement initiatives. The software implementation of the proposed algorithm demonstrates its usage for similarity measurement in a database of business process models. Experiments show that the developed algorithm is 31% faster than a search based on the SQL LIKE clause and allows finding 18% more similar models in the business process model database.http://samit.khpi.edu.ua/article/view/284718business process modeldatabase of business process modelsnatural language processingsimilarity measurement algorithmactivity labelssoftware implementation of the algorithm |
| spellingShingle | Kopp Andrii Dmytro Orlovskyi АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ Вісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології business process model database of business process models natural language processing similarity measurement algorithm activity labels software implementation of the algorithm |
| title | АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ |
| title_full | АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ |
| title_fullStr | АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ |
| title_full_unstemmed | АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ |
| title_short | АЛГОРИТМ ВИМІРЮВАННЯ ПОДІБНОСТІ МІТОК ДІЯЛЬНОСТЕЙ НА ОСНОВІ NLP У БАЗІ ДАНИХ МОДЕЛЕЙ БІЗНЕС-ПРОЦЕСІВ |
| title_sort | алгоритм вимірювання подібності міток діяльностей на основі nlp у базі даних моделей бізнес процесів |
| topic | business process model database of business process models natural language processing similarity measurement algorithm activity labels software implementation of the algorithm |
| url | http://samit.khpi.edu.ua/article/view/284718 |
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